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MLModel using the data files and the recipe as information
sources.
An MLModel is nearly immutable. Users can only update the MLModelName
and the ScoreThreshold in an MLModel without creating a
new MLModel.
CreateMLModel is an asynchronous operation. In response to CreateMLModel,
Amazon Machine Learning (Amazon ML) immediately returns and sets the MLModel
status to PENDING. After the MLModel is created and ready
for use, Amazon ML sets the status to COMPLETED.
You can use the GetMLModel operation to check progress of the MLModel
during the creation operation.
CreateMLModel requires a DataSource with computed statistics,
which can be created by setting ComputeStatistics to true
in CreateDataSourceFromRDS, CreateDataSourceFromS3, or CreateDataSourceFromRedshift
operations.
Namespace: Amazon.MachineLearning
Assembly: AWSSDK.dll
Version: (assembly version)
public abstract CreateMLModelResponse CreateMLModel( CreateMLModelRequest request )
Container for the necessary parameters to execute the CreateMLModel service method.
| Exception | Condition |
|---|---|
| IdempotentParameterMismatchException | A second request to use or change an object was not allowed. This can result from retrying a request using a parameter that was not present in the original request. |
| InternalServerException | An error on the server occurred when trying to process a request. |
| InvalidInputException | An error on the client occurred. Typically, the cause is an invalid input value. |
.NET Framework:
Supported in: 4.5, 4.0, 3.5